Triple

T33325766
Position Surface form Disambiguated ID Type / Status
Subject Kufa school of Quranic recitation E853258 entity
Predicate hasNotableReciter P177700 FINISHED
Object Hamzah az-Zayyat
Hamzah az-Zayyat was a prominent early Muslim scholar and one of the seven canonical Qur’anic reciters, renowned for his influential reading tradition transmitted from Kufa.
E2064447 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Hamzah az-Zayyat | Statement: [Kufa school of Quranic recitation, hasNotableReciter, Hamzah az-Zayyat]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hamzah az-Zayyat
Triple: [Kufa school of Quranic recitation, hasNotableReciter, Hamzah az-Zayyat]
Generated description
Hamzah az-Zayyat was a prominent early Muslim scholar and one of the seven canonical Qur’anic reciters, renowned for his influential reading tradition transmitted from Kufa.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f349685f088190b8fda44083a018a9 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_6a01b02441648190adafb4ad0c1d9cdf completed May 11, 2026, 10:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a365c56779c81908eb5892df750aa94 completed June 20, 2026, 9:24 a.m.
NEDg Description generation batch_6a365d415b94819095be28ce74f2e717 completed June 20, 2026, 9:28 a.m.
NED2 Entity disambiguation (via description) batch_6a365db10b648190a22055323a8393f3 completed June 20, 2026, 9:30 a.m.
Created at: May 1, 2026, 1:33 a.m.